Eric Dexheimer (@eric_dexheimer) header
Eric Dexheimer (@eric_dexheimer) profile picture

PhD student at Dyson Robotics Lab, Imperial College London

London, UK
Joined March 2022
Photo by Eric Dexheimer (@eric_dexheimer)Photo by Eric Dexheimer (@eric_dexheimer)Photo by Eric Dexheimer (@eric_dexheimer)Photo by Eric Dexheimer (@eric_dexheimer)Photo by Eric Dexheimer (@eric_dexheimer)Photo by Eric Dexheimer (@eric_dexheimer)Photo by Eric Dexheimer (@eric_dexheimer)Photo by Eric Dexheimer (@eric_dexheimer)Photo by Eric Dexheimer (@eric_dexheimer)
We’ve had fun testing the limits of MASt3R-SLAM on in-the-wild videos. Here’s the drone video of a Minnesota bowling alley that we’ve always wanted to reconstruct! Different scene scales, dynamic objects, specular surfaces, and fast motion.
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The Mila Robot Learning Seminar returns this Thursday (Oct 15, 11am ET) with Eric Dexheimer (Imperial College London) @eric_dexheimer for his talk "Geometric Priors for Dense SLAM." Livestream: youtube.com/watch?v=tuEzO1mB…
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Eric Dexheimer retweeted
AgentSTAR is an agentic method for both reconstruction and tracking of articulated objects from monocular videos. We can now track through rapid motion, severe occlusion and thin objects! 

There’s no spoon but we can still track it 🥄
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Eric Dexheimer retweeted
I'll be presenting our work at #ECCV2026 in Malmö! 🇸🇪 Find me at the poster and demo sessions: Poster 📅 Thu 10 Sep, 10:30 📍 ExHall #272 Demo 📅 Sat 12 Sep, 8:00 📍 ExHall Also at NeuSLAM Workshop 🤖: Tue 8 Sep, 14:00, Malmö Arena Hotel
(1/3) I am happy to share our work on Triangle Splatting SLAM! We show the first RGB-D SLAM to use differentiable triangles as a 3D map representation. Our method enables online mesh-based deformations and collision checking via on-the-fly Delaunay triangulation.
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Eric Dexheimer retweeted
Excited to share VidMap! #ECCV2026 We bring the temporal structure of SLAM into global SfM for accurate 3D reconstruction of long, unconstrained videos. 🚀 Code: github.com/cvg/vidmap 📄 Paper: arxiv.org/abs/2607.27194 🎥 Video: youtu.be/gy4szd3q5Oo With @pesarlin & @mapo1
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Eric Dexheimer retweeted
Just announced: #CVPR2026 Best Demo Award for KV-Tracker. Congrats to Marwan and co-authors. And thanks to @deepfry_n, @shinjeong99 for massive help running the demo. That's 4 CVPR Best Demo Awards/Honourable Mentions in 3 years for our lab at Imperial! Proud of our demo culture.
How can we run reconstruction models like π³ and Depth Anything 3 in real-time? We present KV-Tracker, a training-free approach, for real-time tracking of scenes and objects. Achieving up to 30 FPS! With @alzugarayign, @makezur, @XinKong_IC and @AjdDavison
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Eric Dexheimer retweeted
Come check out V-DPM @CVPR [Poster 25] 11:45 - 13:45 4D video reconstruction in the wild: code and models available 🤖 @EldarIsTyping @Oxford_VGG
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Eric Dexheimer retweeted
Come and see a live demo of @marwan_ptr's KV-Tracker: Real-Time Pose Tracking with Transformers *now* in the exhibition hall (at the back, not far from the Lambda booth). @deepfry_n at the controls! #CVPR2026
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Eric Dexheimer retweeted
(1/3) I am happy to share our work on Triangle Splatting SLAM! We show the first RGB-D SLAM to use differentiable triangles as a 3D map representation. Our method enables online mesh-based deformations and collision checking via on-the-fly Delaunay triangulation.
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Eric Dexheimer retweeted
Introducing VGGT-Ω: scaling feed-forward reconstruction across static and dynamic scenes, and studying whether the learned geometric representations transfer beyond reconstruction.
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Eric Dexheimer retweeted
I've migrated the old Mast3r-SLAM example I had made last year to the latest version of @rerundotio and made a bunch of improvements! I wanted to spend some time with agents to modernize it. Here's an example of me walking around with my iPhone and getting a dense reconstruction at about 10FPS on a 5090. Heres the following improvements I made. Brought it into the monorepo with proper packaging: • Using @prefix_dev pixi-build to get rid of all the mast3r/asmk/lietorch vendored code with just a few small patches. This let me remove so 60k lines of code from the repo! • Don't have to build the lietorch code on my machine anymore, which was taking ~10 minutes to compile (and also made it work on blackwell when it previously did not) Rebuilt the @Gradio interface: • Fixed incremental updates, .MOV uploads, and stop behavior • Made the CLI + Gradio interface share the same entry point so updates automatically propagate Upgraded the @rerundotio integration: • Switched to a multiprocessing async logging strategy • Added video/pointmap/confidence logging • Improved blueprint layout and hid noisy entities from 3D view • Biggest perf win was the async background logger - documented about a ~2.5x speedup from decoupling logging from tracking The newest and most interesting part was my attempt to replace the CUDA kernels for Gauss-Newton ray matching with a @Modular Mojo backend. As a Python dev, every time I look at CUDA code I basically shy away as it's pretty difficult for me to understand. Mojo let me rewrite the matching logic in a syntax I'm more comfortable with while still getting near-CUDA performance. Mojo is now the default matching backend with CUDA fallback. One major piece that's missing is the custom PyTorch op path, but I'll eventually do that as well. I heavily leaned on Claude Code to do the CUDA → Mojo migration, and I have no doubt it's not the cleanest or most idiomatic, BUT it's way more readable for me and helps me better understand the underlying algorithm. This was a ton of work, and a large part of why I'm doing it is how the monorepo compounds. This becomes an artifact for the next example I want to build with Claude that I can point to, which will make it even faster to implement. The compounding nature of this is really interesting and part of why I'm spending so much time trying to make things nice and readable.
We have HOT3D! I've started using Claude to port more datasets into @rerundotio and exoego-forge. I'd been meaning to bring in the HOT3D dataset from Meta for a while, but with Claude, it's way easier. My goal is to take any egocentric, exocentric, or both datasets and ingest them into a standardized schema. Getting everything into Rerun means we can easily query and transform data via the in-memory OSS server. This lets us generate SQL-like queries such as: "Find me all frames that only contain left hands in the leftmost camera view." Most people think of Rerun as a viewer, but this is the actual superpower. So far we have: 1. HOT3D 2. Hocap 3. UmeTrack 4. Assembly101 5. EgoDex Planning to add more, and with every addition, it gets easier as we build up agent skills and better code examples. Hoping to make it almost fully automatic for adding new datasets. The next few I'm looking at are Harmony4D and Aria Pilot Gen2 After we have enough samples, I'll work on bringing in all the different algorithms I've worked on to transform the data 🙂
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Eric Dexheimer retweeted
On Sensor Vision Workshop at #CVPR2026. New deadline for abstracts and demos: 10th April; we welcome submissions of work-in-progress or work published elsewhere. Come and discuss the future of ultra-efficient computer vision on the edge, where pixels and processing come together.
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Eric Dexheimer retweeted
📢📢📢 I’ve been watching @veritasium since high school, so it’s surreal to see our work Flying with Photons featured in their video! FWP allows "flying" in the scene while seeing light propagate.
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Eric Dexheimer retweeted
Introducing V-DPM, for 4D reconstruction of in-the-wild videos. We build on top of VGGT, using Dynamic Point Maps for jointly representing 3D and motion. Joint work with: @EldarIsTyping , @LaiZihang , and Andrea Vedaldi. @Oxford_VGG. Check out the demo and code 👇
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Eric Dexheimer retweeted
Photoreal 3D digital twins of vast natural habitats, this is whats coming! It's been a fruitful journey so far attempting to bring reefs from the water to tangible digital assets you can interact with. Access the demo here: ben-williams-ai.github.io/
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Eric Dexheimer retweeted
Introducing 4D Primitive-Mâché (4DPM), a new method for replayable 4D reconstruction from monocular videos. We split dynamic scenes into 3D primitives and recover their motion. 4DPM can infer object positions even after they leave view. Joint work with @marwan_ptr @AjdDavison
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Excited to present ACE-SLAM, the first neural SLAM to use Scene Coordinate Regression as an implicit map representation Efficient (real-time from live stream), compressive (neural maps <1MB) and robust to dynamic scenes With @marwan_ptr and @AjdDavison ialzugaray.github.io/ace-sla…
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Eric Dexheimer retweeted
Genie3 is a real-time, interactive and general world model! Excited to see it used for training agents. It's also really fun to play around with.
#Genie3 is a real, interactive, playable experience. We're having so much fun with it at work---in between meetings, during breaks. Here's @RuiqiGao, @joeaortiz, @ChrisWu6080 following a pack of polar bears through a New York City street! Check out more on the webpage: goo.gle/genie-3
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Eric Dexheimer retweeted
July has been a big month for Viser! - Released v1.0.0😊 - We did some writing Some demos👇
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Eric Dexheimer retweeted
Good essay on the analogy of the stone soup tale to AI misconception. More emphasis is placed on individual AI models and teams/algorithms who made them, rather than on the collective effort to generate big data, the most important ingredient of the soup. simons.berkeley.edu/news/sto…
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Eric Dexheimer retweeted
Well done to Riku and @eric_dexheimer on Best Demo Honourable Mention for MASt3R-SLAM at #CVPR2025. That's 3 best demo awards in the past 2 years at CVPR from our lab! (Gaussian Splatting SLAM won Best Demo in 2024 and SuperPrimitive got Honourable Mention). #DemosNotTables
We (with @eric_dexheimer) will be demoing MASt3R-SLAM @CVPR today 16:00-18:00, ExHall B, 9 Come and see the limits of our real-time monocular dense SLAM! We’ll also be presenting our poster #83 on Sat 14th from 17:00-19:00. See you soon!
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